In the semiconductor industry, devices are fabricated by a number of manufacturing processes producing structures of an ever-decreasing size. Thus, manufacturing processes, such as inspection, metrology, and review processes require increased precision and effectiveness for manufacturing specimens. The term “specimen” used in this specification should be expansively construed to cover any kind of wafer, reticle and other structures, combinations and/or parts thereof used for manufacturing semiconductor integrated circuits, magnetic heads, flat panel displays, and other thin film devices.
Manufacturing processes, such as inspection, metrology, and review of specimens, can include recognition of structural elements, measuring, calibration, monitoring, inspection, review and analyses of defects, reporting and/or other procedures necessary for evaluating parameters and/or conditions of respective manufacturing processes and providing necessary feedback. A variety of manufacturing tools can be based on non-destructive observations as, by way of non-limiting example, scanning electron microscopes, atomic force microscopes, optical inspection tools and others, and used for inspection, metrology, and review processes. As manufacture control requirements become more challenging, recipe generation for processes, such as inspection, metrology and review processes, has also become highly complex.
The volume of measurements and the complexity of recipes in state-of-the-art specimen manufacturing have made the conventional manual (or semi-manual) process of creating the recipes increasingly problematic. Emerging techniques of automated recipe generation can improve production time and development, and reduce chances of errors.
Problems of automated recipe generation have been recognized in the conventional art and various systems have been developed to provide solutions. For example, a conventional system for creating an inspection recipe includes an inspection target selection module selecting an inspection target; a critical area extraction module extracting corresponding critical areas for defect sizes in the inspection target; a defect density prediction module extracting corresponding defect densities predicted by defects to be detected in the inspection target for the defect sizes; a killer defect calculation module calculating corresponding numbers of killer defects in the defect sizes based on the critical areas and the defect densities; and a detection expectation calculation module calculating the number of killer defects expected to be detected for prospective inspection recipes determining rates of defect detection for the defect sizes, based on the number of killer defects and the rates of defect detection prescribed in the prospective inspection recipes.
Another conventional method for creating an inspection recipe includes acquiring a first design and one or more characteristics of output of an inspection system for a wafer on which the first design is printed using a manufacturing process. The method also includes creating an inspection recipe for a second design using the first design and the one or more characteristics of the output acquired for the wafer on which the first design is printed. The first and second designs are different. The inspection recipe will be used for inspecting wafers after the second design is printed on the wafers using the manufacturing process.
Conventional recipe generations solutions generate recipes based on wafers that have been produced. Traditional solutions rely on a first wafer to be manufactured, capture an image of the wafer, examine the produced wafer, and generate a recipe based on the analysis of the examined wafer. Typically, a user inputs data from the produced wafer to generate a recipe. Thus, the recipe generation process in existing solutions is a time consuming and cumbersome process.